Application of Decomposition Methods in the Filtering of Event-Related Potentials
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The processes giving rise to an event-related potential engage several evoked and induced oscillatory components, which reflect phase or nonphase locked activity throughout the multiple trials of an experiment. The separation and identification of such components could not only serve diagnostic purposes but also facilitate the design of brain–computer interface systems. However, the effective analysis of components is hindered by many factors including the complexity of the EEG signal and its variation over the trials. In this chapter, we study several measures for the identification of the nature of independent components and propose a complete methodology for efficient decomposition of the rich information content embedded in the multichannel EEG recordings associated with the multiple trials of an event-related experiment. The efficiency of the proposed methodology is demonstrated through simulated and real experiments.
KeywordsIndependent Component Analysis Event Related Potential Independent Component Analysis Event Related Desynchronization Independent Component Analysis Component
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Present work was supported by a research fund from the Research Committee of the Technical University of Crete. The authors would like to thank Prof. Cristin Bigan at the Ecological University of Bucharest, Romania for kindly providing the EEG dataset.
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